Potential of E-Learning Interventions and Artificial Intelligence-Assisted Contouring Skills in Radiotherapy: The ELAISA Study

被引：0

作者：

Rasmussen, Mathis Ersted ^{[1
]}

Akbarov, Kamal ^{[2
]}

Titovich, Egor ^{[2
]}

Nijkamp, Jasper Albertus ^{[3
]}

Van Elmpt, Wouter ^{[4
]}

Primdahl, Hanne ^{[5
]}

Lassen, Pernille ^{[5
]}

Cacicedo, Jon ^{[6
]}

Cordero-Mendez, Lisbeth ^{[2
]}

Uddin, A. F. M. Kamal ^{[7
]}

Mohamed, Ahmed ^{[8
]}

Prajogi, Ben ^{[9
]}

Brohet, Kartika Erida ^{[10
]}

Nyongesa, Catherine ^{[11
]}

Lomidze, Darejan ^{[12
,13
]}

Prasiko, Gisupnikha ^{[14
]}

Ferraris, Gustavo ^{[15
]}

Mahmood, Humera ^{[16
]}

Stojkovski, Igor ^{[17
]}

Isayev, Isa ^{[18
]}

Mohamad, Issa ^{[19
]}

Shirley, Leivon ^{[20
]}

Kochbati, Lotfi ^{[21
]}

Eftodiev, Ludmila ^{[22
]}

Piatkevich, Maksim ^{[23
]}

Jara, Maria Matilde Bonilla ^{[24
]}

Spahiu, Orges ^{[25
]}

Aralbayev, Rakhat ^{[26
]}

Zakirova, Raushan ^{[27
]}

Subramaniam, Sandya ^{[28
]}

Kibudde, Solomon ^{[29
]}

Tsegmed, Uranchimeg ^{[30
]}

Korreman, Stine Sofia ^{[3
]}

Eriksen, Jesper Grau ^{[1
]}

机构：

[1] Aarhus Univ Hosp, Expt Clin Oncol, Aarhus, Denmark

[2] IAEA, Vienna, Austria

[3] Aarhus Univ, Dept Clin Med, Aarhus, Denmark

[4] Maastricht Univ, MAASTRO Clin, Med Ctr, Maastricht, Netherlands

[5] Aarhus Univ Hosp, Dept Oncol, Aarhus, Denmark

[6] Cruces Univ Hosp, Dept Radiat Oncol, Bilbao, Spain

[7] Labaid Canc Hosp & Super Special Ctr, Dhaka, Bangladesh

[8] Univ Gezira, Natl Canc Inst, Wad Madani, Sudan

[9] Cipto Mangunkusumo Hosp, Jakarta, Indonesia

[10] Dharmais Canc Hosp, Jakarta, Indonesia

[11] Kenyatta Natl Hosp, Nairobi, Kenya

[12] Tbilisi State Med Univ, Tbilisi, Georgia

[13] Ingorokva High Med Technol Univ Clin, Tbilisi, Georgia

[14] Nepal Canc Hosp & Res Ctr, Lalitpur, Nepal

[15] Ctr Radioterapiya dean Funes, Cordoba, Argentina

[16] Atom Energy Canc Hosp NORI, Islamabad, Pakistan

[17] Univ Clin Radiotherapy & Oncol, Skopje, North Macedonia

[18] Natl Ctr Oncol, Baku, Azerbaijan

[19] King Hussein Canc Ctr, Amman, Jordan

[20] Christian Inst Hlth Sci & Res, Dimapur, India

[21] Hosp Abderrahmen Mami, Ariana, Tunisia

[22] Moldavian Oncol Inst, Kishinev, Moldova

[23] NN Alexandrov Natl Canc Ctr Belarus, Minsk, BELARUS

[24] Hosp Mexico, San Jose, Costa Rica

[25] Mother Tereza Hosp, Tirana, Albania

[26] Natl Ctr Oncol & Hematol, Bishkek, Kyrgyzstan

[27] Ctr Nucl Med & Oncol, Semey, Kazakhstan

[28] Hosp Kuala Lumpur, Kuala Lumpur, Malaysia

[29] Uganda Canc Inst, Kampala, Uganda

[30] Natl Canc Ctr Mongolia, Ulaanbaatar, Mongolia

来源：

JCO GLOBAL ONCOLOGY | 2024年 / 10卷

关键词：

VOLUME DELINEATION; SEGMENTATION; ORGANS; RISK; CONSISTENCY; EFFICIENCY; SYSTEM; REDUCE; BRAIN; COST;

D O I：

10.1200/GO.24.00173

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

PURPOSEMost research on artificial intelligence-based auto-contouring as template (AI-assisted contouring) for organs-at-risk (OARs) stem from high-income countries. The effect and safety are, however, likely to depend on local factors. This study aimed to investigate the effects of AI-assisted contouring and teaching on contouring time and contour quality among radiation oncologists (ROs) working in low- and middle-income countries (LMICs).MATERIALS AND METHODSNinety-seven ROs were randomly assigned to either manual or AI-assisted contouring of eight OARs for two head-and-neck cancer cases with an in-between teaching session on contouring guidelines. Thereby, the effect of teaching (yes/no) and AI-assisted contouring (yes/no) was quantified. Second, ROs completed short-term and long-term follow-up cases all using AI assistance. Contour quality was quantified with Dice Similarity Coefficient (DSC) between ROs' contours and expert consensus contours. Groups were compared using absolute differences in medians with 95% CIs.RESULTSAI-assisted contouring without previous teaching increased absolute DSC for optic nerve (by 0.05 [0.01; 0.10]), oral cavity (0.10 [0.06; 0.13]), parotid (0.07 [0.05; 0.12]), spinal cord (0.04 [0.01; 0.06]), and mandible (0.02 [0.01; 0.03]). Contouring time decreased for brain stem (-1.41 [-2.44; -0.25]), mandible (-6.60 [-8.09; -3.35]), optic nerve (-0.19 [-0.47; -0.02]), parotid (-1.80 [-2.66; -0.32]), and thyroid (-1.03 [-2.18; -0.05]). Without AI-assisted contouring, teaching increased DSC for oral cavity (0.05 [0.01; 0.09]) and thyroid (0.04 [0.02; 0.07]), and contouring time increased for mandible (2.36 [-0.51; 5.14]), oral cavity (1.42 [-0.08; 4.14]), and thyroid (1.60 [-0.04; 2.22]).CONCLUSIONThe study suggested that AI-assisted contouring is safe and beneficial to ROs working in LMICs. Prospective clinical trials on AI-assisted contouring should, however, be conducted upon clinical implementation to confirm the effects. AI improves contouring quality and saves time for oncologists in low- and middle-income countries.

引用

页数：11

共 17 条

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